Shallow Crustal Structure Beneath Taal Volcano, Philippines, Revealed by the 1993 Seismic Explosion Survey

We carried out an seismic explosion survey at Taal volcano in March, 1993. The explosions were done at the west of the volcanic island and digital event recorders were deployed along a fan-shooting survey line at the east of the volcanic island and also along a short straight survey line across the island. Small-aperture arrays were also operated at two sites west of the volcanic island. We found that P waves that traveled just beneath the main crater strongly attenuated and showed later arrivals. This result suggests the existence of a low-velocity and low-Q region around the main crater at a depth of about 1.5km, although the location and extent cannot be determined exactly. P wave velocity of this abnormal region may be eatimated to be lower than that of the surroundings by much greater than about 25%, if we assume the region is restricted just beneath the main crater. We applied the NMO correction to the later part of seismograms and found a reflector around the east of the main crater at a depth of about 6km, which may suggest the top surface of the magma reservoir

CCG Starter Data Kit: Mauritania

A starter data kit for Mauritani

CCG Starter Data Kit: Papua New Guinea

A starter data kit for Papua New Guine

Selected ‘Starter Kit’ energy system modelling data for South Africa (#CCG)

Energy system modelling can be used to assess the implications of different scenarios and support improved policymaking. However, access to data is often a barrier to starting energy system modelling in developing countries, thereby causing delays. Therefore, this article provides data that can be used to create a simple zero order energy system model for South Africa, which can act as a starting point for further model development and scenario analysis. The data are collected entirely from publicly available and accessible sources, including the websites and databases of international organizations, journal articles, and existing modelling studies. This means that the dataset can be easily updated based on the latest available information or more detailed and accurate local data. These data were also used to calibrate a simple energy system model using the Open Source Energy Modelling System (OSeMOSYS) and two stylized scenarios (Fossil Future and Least Cost) for 2020–2050. The assumptions used and results of these scenarios are presented in the appendix as an illustrative example of what can be done with these data. This simple model can be adapted and further developed by in-country analysts and academics, providing a platform for future work

Selected ‘Starter Kit’ energy system modelling data for Mauritania (#CCG)

Energy system modelling can be used to assess the implications of different scenarios and support improved policymaking. However, access to data is often a barrier to starting energy system modelling in developing countries, thereby causing delays. This article therefore provides data that can be used to create a simple zero order energy system model for Mauritania, which can act as a starting point for further model development and scenario analysis. The data are collected entirely from publicly available and accessible sources, including the websites and databases of international organizations, journal articles, and existing modelling studies. This means that the dataset can be easily updated based on the latest available information or more detailed and accurate local data. These data were also used to calibrate a simple energy system model using the Open Source Energy Modelling System (OSeMOSYS) and two stylized scenarios (Fossil Future and Least Cost ) for 2020-2050. The assumptions used and results of these scenarios are presented in the appendix as an illustrative example of what can be done with these data. This simple model can be adapted and further developed by in-country analysts and academics, providing a platform for future work

Selected ‘Starter Kit’ energy system modelling data for Equatorial Guinea (#CCG)

Energy system modelling can be used to assess the implications of different scenarios and support improved policymaking. However, access to data is often a barrier to starting energy system modelling in developing countries, thereby causing delays. Therefore, this article provides data that can be used to create a simple zero order energy system model for Equatorial Guinea, which can act as a starting point for further model development and scenario analysis. The data are collected entirely from publicly available and accessible sources, including the websites and databases of international organizations, journal articles, and existing modelling studies. This means that the dataset can be easily updated based on the latest available information or more detailed and accurate local data. These data were also used to calibrate a simple energy system model using the Open Source Energy Modelling System (OSeMOSYS) and two stylized scenarios (Fossil Future and Least Cost) for 2020-2050. The assumptions used and results of these scenarios are presented in the appendix as an illustrative example of what can be done with these data. This simple model can be adapted and further developed by in-country analysts and academics, providing a platform for future work

Selected 'Starter Kit' energy system modelling data for Angola (#CCG)

Energy system modelling can be used to assess the implications of different scenarios and support improved policymaking. However, access to data is often a barrier to starting energy system modelling in developing countries, thereby causing delays. This article therefore provides data that can be used to create a simple zero order energy system model for Angola, which can act as a starting point for further model development and scenario analysis. The data are collected entirely from publicly available and accessible sources, including the websites and databases of international organizations, journal articles, and existing modelling studies. This means that the dataset can be easily updated based on the latest available information or more detailed and accurate local data. These data were also used to calibrate a simple energy system model using the Open Source Energy Modelling System (OSeMOSYS) and two stylized scenarios (Fossil Future and Least Cost) for 2020–2050. The assumptions used and results of these scenarios are presented in the appendix as an illustrative example of what can be done with these data. This simple model can be adapted and further developed by in-country analysts and academics, providing a platform for future work

Selected ‘Starter Kit’ energy system modelling data for Liberia (#CCG)

Energy system modelling can be used to assess the implications of different scenarios and support improved policymaking. However, access to data is often a barrier to starting energy system modelling in developing countries, thereby causing delays. Therefore, this article provides data that can be used to create a simple zero order energy system model for Liberia, which can act as a starting point for further model development and scenario analysis. The data are collected entirely from publicly available and accessible sources, including the websites and databases of international organizations, journal articles, and existing modelling studies. This means that the dataset can be easily updated based on the latest available information or more detailed and accurate local data. These data were also used to calibrate a simple energy system model using the Open Source Energy Modelling System (OSeMOSYS) and two stylized scenarios (Fossil Future and Least Cost) for 2020–2050. The assumptions used and results of these scenarios are presented in the appendix as an illustrative example of what can be done with these data. This simple model can be adapted and further developed by in-country analysts and academics, providing a platform for future work